Abstract Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size (?7 mm or ?5 mm). However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imagining on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. In previous studies, we found that patients with and without IAs have RNA expression differences in their circulating blood that reflect leukocyte activation and inflammatory signaling. Expression differences could both identify the presence of IAs and stratify IA samples by size. We therefore hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. In this Phase-I study, we propose to use whole blood transcriptomes to develop a ?one- stop? diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to: 1) Develop and validate biomarkers to predict risk indicated by the currently-used size metric, 2) Develop and validate biomarkers to predict risk indicated by the clinical PHASES score, and 2) Develop and validate biomarkers to predict risk indicated by the RRS. These biomarkers will save the healthcare millions in unnecessary high-cost imaging procedures and unnecessary aneurysm treatments.